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Phys.org

Matcha model makes drug candidate screening more than 30 times faster

Matcha model makes drug candidate screening more than 30 times faster
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Ligand Pro, founded by Skoltech professors and a Skoltech Ph.D. student, has presented Matcha, an AI-powered molecular docking model that performs virtual drug screening 30 times faster than the large co-folding models of the AlphaFold class developed by Nobel laureates, while surpassing them in both accuracy and physical correctness of the results. Matcha opens up new possibilities for virtual sc

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